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dc.contributor.authorLabus, Jerkoen
dc.contributor.authorKorolija, Ivanen
dc.contributor.authorMarjanovic-Halburd, Ljiljanaen
dc.contributor.authorZhang, Yien
dc.contributor.authorCoronas, Albertoen
dc.date.accessioned2013-10-09T10:40:01Z
dc.date.available2013-10-09T10:40:01Z
dc.date.issued2012
dc.identifier.citationLabus, J., Korolija, I., Marjanovic-Halburd, L., Zhang, Y. and Coronas, A. (2012) ANN application to modelling and control of small absorption chillers. BSO12 - Building Simulation and Optimization Conference. Loughborough, UK, pp. 245–252.en
dc.identifier.urihttp://hdl.handle.net/2086/9146
dc.description.abstractThe main aim of this paper is to demonstrate the application of Artificial Neural Networks (ANN) in small absorption chillers modelling and their control optimisation. The Genetic Algorithms (GA) optimisation method was coupled to the ANN model in order to solve the optimal operation problem where the objective function was the minimal primary energy consumption. This paper analyses the impact of control strategy on energy performance of small capacity absorption chillers, while emphasizing the usability of ANN model, and comparing this strategy to conventional operation strategies.en
dc.language.isoenen
dc.titleANN application to modelling and control of small absorption chillersen
dc.typeConferenceen
dc.researchgroupInstitute of Energy and Sustainable Developmenten
dc.peerreviewedYesen
dc.fundern/aen
dc.projectidn/aen
dc.researchinstituteInstitute of Energy and Sustainable Development (IESD)en


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